{"id":"W2767869150","doi":"10.4018/ijebr.2018010104","title":"Review Spam Detection by Highlighting Potential Spammers and Diminishing Their Effect","year":2017,"lang":"en","type":"article","venue":"International Journal of E-Business Research","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Exploit; Popularity; Competitor analysis; Order (exchange); Product (mathematics); Internet privacy; Service (business); Computer science; Business; Marketing; Computer security; Psychology; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003412635,0.0001171688,0.0002083646,0.0002941402,0.0005475931,0.001497724,0.001828411,0.00006444137,0.00001972801],"category_scores_gemma":[0.0017541,0.00008955193,0.00008326826,0.0001854092,0.0001125159,0.001916296,0.0004956883,0.0005047845,0.000008159494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001073755,"about_ca_system_score_gemma":0.00006506433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000186666,"about_ca_topic_score_gemma":0.00000971188,"domain_scores_codex":[0.99791,0.0002624231,0.0003406547,0.0002287938,0.001026777,0.0002314131],"domain_scores_gemma":[0.997159,0.0002857836,0.0004542786,0.0003134637,0.001680003,0.00010745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002124746,0.00008684109,0.00242119,0.0002995981,0.0002091961,0.0002874783,0.000188333,0.0000475681,0.09412143,0.0002725307,0.008601496,0.8932518],"study_design_scores_gemma":[0.01103558,0.003187141,0.2009286,0.02581159,0.0002024421,0.01707895,0.0001829778,0.06686111,0.3649547,0.009291657,0.2982203,0.002244903],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5566496,0.01880477,0.3711203,0.03938283,0.01135945,0.0004785061,0.000008476878,0.00006155736,0.002134479],"genre_scores_gemma":[0.9926848,0.005918426,0.0004255097,0.0001192843,0.0007602696,0.000004111253,0.000001089981,0.00001011433,0.00007636751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8910069,"threshold_uncertainty_score":0.9995388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04172126503389524,"score_gpt":0.3643047750472569,"score_spread":0.3225835100133617,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}